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What Affects Debt Enforcement Proceedings? Evidence from the Czech Republic Cover

What Affects Debt Enforcement Proceedings? Evidence from the Czech Republic

Open Access
|Jun 2023

Abstract

This paper aims to identify the factors contributing to the unusually high prevalence of over-indebtedness and debt enforcement proceedings in the Czech Republic at the granular geographic level of extended-powers municipalities (ORP). The main reason for this level is simple, not to lose information about differences among the municipalities, since there is quite a sharp contrast even within the same regions. The dependent variable is the share of people with one or more debt enforcement proceedings outstanding against them. We employ a set of explanatory variables including long-term unemployment, socially excluded localities, regional GDP per capita, education level, and a proxy for distance to the local economic center. The results are estimated using panel data regression with random effects, due to the time-invariant nature of certain variables. Because of poor data availability for some variables at this highly localized level, we make several assumptions; for example, we transfer the regional GDP per capita values to all ORPs in the region. Similar problems arise with education level, where we use data from the 2011 national census. Even with these data restrictions, our set of explanatory variables is shown to be statistically significant with the expected coefficient signs. GDP per capita and higher education level have a negative impact on the prevalence of debt enforcement proceedings, while long-term unemployment, the number of socially excluded localities in the area, and the distance-to-center proxy have a positive effect.

DOI: https://doi.org/10.2478/revecp-2023-0003 | Journal eISSN: 1804-1663 | Journal ISSN: 1213-2446
Language: English
Page range: 89 - 103
Submitted on: Jul 11, 2022
Accepted on: Feb 3, 2023
Published on: Jun 20, 2023
Published by: Mendel University in Brno
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2023 Daniel Pakši, Milan Šimek, Jakub Vontroba, published by Mendel University in Brno
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.